Field Evaluation of DRAINMOD 5.1 Under a Cold Climate: Simulation of Daily Midspan Water Table Depths and Drain Outflows1

Abstract: The hydrologic performance of DRAINMOD 5.1 was assessed for the southern Quebec region considering freezing/thawing conditions. A tile drained agricultural field in the Pike River watershed was instrumented to measure tile drainage volumes. The model was calibrated using water table depth and subsurface flow data over a two‐year period, while another two‐year dataset served to validate the model. DRAINMOD 5.1 accurately simulated the timing and magnitude of subsurface drainage events. The model also simulated the pattern of water table fluctuations with a good degree of accuracy. The R² between the observed and simulated daily WTD for calibration was >0.78, and that for validation was 0.93. The corresponding coefficients of efficiency (E) were >0.74 and 0.31. The R² and E values for calibration/validation of subsurface flow were 0.73/0.48 and 0.72/0.40, respectively. DRAINMOD simulated monthly subsurface flow quite accurately (E > 0.82 and R² > 0.84). The model precisely simulated daily/monthly drain flow over the entire year, including the winter months. Thus DRAINMOD 5.1 performed well in simulating the hydrology of a cold region.     

The environment as a factor of production

This paper uses firm-level data about electric utilities to develop an empirical model of how electric utilities use and bank SO₂ pollution permits under the Acid Rain Program. The empirical model considers emissions, fuels, and labor as variable inputs with quasi-fixed stocks of permits and capital. Consequently, substitution possibilities between the environment and other production factors can be measured and tested. The results reveal substantial substitution between emissions, permit stocks, capital, fuel, and labor. The empirical findings also indicate that firms bank permits primarily as a hedge against uncertainty and for other firm-specific reasons. Overall, the results suggest that cap-and-trade approaches can reduce the cost of meeting environmental goals by providing a mechanism for addressing regulatory and market risks and by signaling an appropriate price for factor use, especially irreversible capital investments.     

Inexact fuzzy-stochastic constraint-softened programming – A case study for waste management

In this study, an inexact fuzzy-stochastic constraint-softened programming method is developed for municipal solid waste (MSW) management under uncertainty. The developed method can deal with multiple uncertainties presented in terms of fuzzy sets, interval values and random variables. Moreover, a number of violation levels for the system constraints are allowed. This is realized through introduction of violation variables to soften system constraints, such that the model’s decision space can be expanded under demanding conditions. This can help generate a range of decision alternatives under various conditions, allowing in-depth analyses of tradeoffs among economic objective, satisfaction degree, and constraint-violation risk. The developed method is applied to a case study of planning a MSW management system. The uncertain and dynamic information can be incorporated within a multi-layer scenario tree; revised decisions are permitted in each time period based on the realized values of uncertain events. Solutions associated with different satisfaction degree levels have been generated, corresponding to different constraint-violation risks. They are useful for supporting decisions of waste flow allocation and system-capacity expansion within a multistage context.     

PeLM: modeling of pesticide-losses through runoff and sediment transport

A GIS-aided pesticide loss model (PeLM) was developed to simulate pesticide losses through surface runoff and sediment transport in watershed systems. The PeLM could tackle the movement of eroded soil along with surface runoff as well as the pesticide losses in adsorbed and dissolved phases. The contributions of different soil types in the sediment were also examined. The model was applied to the Kintore Creek Watershed of southern Ontario, Canada. The simulation results were verified through observed data, indicating a correlation level of 0.89-0.98. The results also showed that clay particles usually held the largest share of contributions to pesticide losses through soil erosion. This study is significant in the efforts for modeling nonpoint source pollution in watershed systems. It provides useful information and support for the related decisions of watershed management.     

Assessment of arsenic and heavy metal concentrations in water and sediments of the Rio Grande at El Paso-Juarez metroplex region

The Rio Grande located along the US-Mexico border is affected by anthropogenic activities along its geographical course. Runoff and wind deposition of smelting residues may contribute to the pollution of the Rio Grande in the El Paso-Ciudad Juarez area. Few studies have addressed the presence or impacts of heavy metals or arsenic in this ecosystem. This study reports a survey of heavy metals (Cr, Cu, Cd, Ni, Pb, and Zn) and arsenic (As) in water and sediments of the Rio Grande collected from seven sites in the El Paso-Juarez region. Since water quality influences metal content in water, physical (temperature, flow and conductivity), and chemical (pH, dissolved oxygen, nitrates, alkalinity, and water hardness) parameters were measured at each site. Arsenic and heavy metal levels were determined using Inductively Couple Plasma (ICP) emission spectroscopy following EPA procedures. Zinc and lead were found as both total and dissolved metals in most of the samples, with concentrations of total recoverable metals reaching up to 105 and 70 microg/l, respectively. Most metals were found in sediment samples collected from four of seven sites. The highest Cu concentration (35 mg/l) was found at the American Dam site. Concentrations of metals found through this survey will be used as a reference for future studies in monitoring arsenic, heavy metals, and their impacts in the Rio Grande.     

A Framework for Comprehensive,Integrated, Watershed Monitoring in New York City

The International Life SciencesInstitute (ILSI) Risk Science Institute (RSI) convenedan expert panel of scientists to developrecommendations for a comprehensive monitoring programfor the Croton and Catskill/Delaware watersheds, whichprovide drinking water to New York City's residents. This effort was conducted as part of efforts topreserve and enhance the quality of New York City'sreservoir system through a watershed protectionprogram. The panel developed recommendations for astrategic framework on which to construct a monitoringprogram. As part of this activity, the paneldetermined whether existing monitoring activities weredeficient and, where activities were deficient, thepanel developed recommendations for additionalinformation that should be collected.The panel recommended the development and use of anintegrated approach to watershed monitoring, whichdraws on modeling, risk-based planning and analysis,statistical sampling and design, and basic compliancemonitoring. The approach should be designed toprovide an assessment of natural and anthropogenicsources of stress to the system as well as anassessment of water quality trends in response tostresses acting in concert, both over the long termand over the five-year New York City Memorandum ofAgreement (MOA) assessment time frame. It should alsoprovide an assessment of the human health andenvironmental risks posed by a variety of stressors,and the impact of management actions implemented toameliorate stressors.     

Policy coherence in climate governance in Caribbean Small Island Developing States

Climate governance in Small Island developing States (SIDS) is a pressing priority to preserve livelihoods, biodiversity and ecosystems for the next generations. Understanding the dynamics of climate change policy integration is becoming more crucial as we try to measure the success of environmental governance efforts and chart new goals for sustainable development. At the international level, climate change policy has evolved from single issue to integrated approaches towards achieving sustainable development. New actors, new mechanisms and institutions of governance with greater fragmentation in governance across sectors and levels (Biermann and Pattberg, 2008) make integration of policy in the area of climate change governance even more of a challenge today. What is the Caribbean reality regarding policy coherence in climate change governance? Are the same climate change policy coherence frameworks useful or indeed applicable for environmental governance in developing states more generally and for SIDS in particular? What are the best triggers to achieve successful climate change policy integration in environmental governance—especially as the complex interconnectivity of new actors, institutions and mechanisms make the process of integration even more challenging? What facilitates and what hampers climate policy integration in the regional Caribbean context? This article reviews the debates around policy coherence for climate change governance, creates a framework to test or measure policy coherence and examines how relevant this has been to regional climate change governance processes in Commonwealth Caribbean States. The study found that though at the regional level, there is substantial recognition of the importance of and mechanics involved in climate policy coherence, this has not translated to policy coherence at the regional and national levels. There is a large degree of fragmentation in the application of climate policy in each Caribbean Island with no mechanism to breach the gap. Silos in public environmental governance architectures, unwillingness to share data, insufficient political will; unsustainable project-based funding and lack of accountability among actors are the main challenges to climate policy coherence. The findings fill a gap in the literature on the elements of climate policy coherence from a SIDS perspective.     

Optimization of anaerobic digestion of municipal solid waste in combined process and sequential staging.

The optimization of anaerobic digestion aims to maximize organic waste stabilization after a short digestion period. This paper presents the optimization performance of the combined anaerobic digestion and sequential staging concept in a thermophilic, solid-state batch system as a treatment technology prior to landfill. The former involves enhanced pre-stage flushing with the addition of microaeration and inoculum in the methane phase. The latter involves leachate cross-recirculation between the mature and fresh waste reactors without conducting a pre-stage operation. The optimized process for combined anaerobic digestion showed that reducing the pre-stage operation with the maximum removal of organics from the waste bed is beneficial. Moreover, the sequential staging concept offers an improved process over the combined anaerobic digestion wherein the specific methane yield of 11.9 and 7.2 L CH4 kg(-1) volatile solids (VS) per day was achieved, respectively. After 28 days of operation, the sequential staging process showed an improved waste stabilization with 86 and 79% mass and volume reduction, respectively. A higher methane yield of 334 L CH4 kg(-1) VS with 86% VS reduction, which is equivalent to 84% process efficiency was obtained.     

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data,PCA, and spatial interpolation

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures.